Method and Device for the Quality Evaluation of a Component Produced by Means of an Additive Manufacturing Method

1. A method for the quality evaluation of a component manufactured by an additive manufacturing method, comprising: providing a component that was produced by an additive manufacturing method; the component having at least one component site; providing an optical imaging device; capturing image data from the at least one component site by the optical imaging device; the image data characterizing the at least one component site of the component produced by an additive manufacturing method; converting the image data into a binary image; providing a structure mask having dimensions less than the binary image; eroding the binary image into a structure image using the structure mask, wherein the erosion comprises a pixel-by-pixel displacement of the structure mask over the binary image and determining whether the structure mask fully fits at a respective site of the binary image, and including the eroded data of the binary image if the structure mask fully fits and excluding the eroded data of the binary image if the structure mask does not fully fit; determining contour data of the structure image; determining at least one image section of the image data that is delimited by the contour data; inspecting the at least one image section for the presence of an image region corresponding to a quality defect; and classifying the component as being qualitatively OK if no quality defect is present, or classifying the component as being qualitatively not OK if a quality defect is present.

2. The method according to claim 1 , wherein the optical imaging device used to detect the image data to be provided is an optical tomography device.

3. The method according to claim 1 , wherein the image data are provided as a composite image computed from a plurality of individual images and/or as a gray-scale image.

4. The method according to claim 1 , wherein the image data are converted into the binary image by using a threshold value method.

5. The method according to claim 4 , wherein a threshold value used in the framework of the threshold value method is chosen so that at least image noise arising from a dark current is eliminated.

6. The method according to claim 1 , wherein a square structure mask is used for eroding the binary image.

7. The method according to claim 1 , wherein, for the inspection of at least one image section for the presence of a quality defect, carrying out at least the following steps: a) providing a first data set, wherein the first data set comprises absolute limit values that each characterize a maximum admissible value range at an associated component site of the component to be produced in the image section; b) detecting a second data set by means of a detection device, wherein the second data set comprises actual values that correspond to the first data set and characterize the associated component site of the component to be produced in the image section; c) comparing the first data set and the second data set by means of a computing device, and c1) classification of the component as being qualitatively fundamentally not OK if at least one actual value lies outside of its associated maximum admissible value range; or c2) classification of the component as being qualitatively fundamentally OK if no actual value lies outside of its associated maximum admissible value range; and if the component has been classified as being qualitatively fundamentally OK; d) providing a third data set, which comprises mean values that are determined by means of the computing device from a plurality of actual values of the second data set, wherein this plurality of actual values characterizes a contiguous region composed of a plurality of component sites; e) determining at least one best-fit function, which is dependent on the component geometry, on the basis of the third data set by means of the computing device; f) determining threshold values, which are dependent on the component geometry, by means of the computing device, wherein the threshold values characterize an admissible scatter range of the actual values around target values specified by the best-fit function; g) checking by means of the computing device whether at least one actual value lies outside of the scatter range characterized by the threshold values; g1) if no actual value lies outside of the scatter range, classification of the component as being qualitatively OK; or g2) if at least one actual value lies outside of the scatter range, combination of all actual values that lie outside of the scatter range in a fifth data set and evaluation of the component quality on the basis of the fifth data set and at least one predetermined quality criterion.

8. The method according to claim 1 , further comprising the following steps for implementing a method for the quality evaluation of a component produced by means of an additive manufacturing method: providing a detection device for determining and providing image data that characterize a component site of the produced component; and providing a computing device, which is coupled to the detection device for the exchange of image data and is designed in such a way as to convert the image data into a binary image, to erode the binary image into a structure image, to determine contour data of the structure image, to determine at least one image section of the image data that are delimited by the contour data, to inspect the at least one image section for the presence of an image region corresponding to a quality defect, and to classify the component as being qualitatively OK if no quality defect is present, or to classify the component as being qualitatively not OK if a quality defect is present.